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Ying Xiao

7 accepted papers

2026

Learning Latent Imaging Biomarkers for Interpretable Microvascular Invasion Prediction in Hepatocellular Carcinoma

AAAI 2026technical

Microvascular invasion (MVI) is a critical prognostic factor that significantly impacts postoperative outcomes in hepatocellular carcinoma (HCC). As the current gold standard for the diagnosis of MVI is based on the postoperative histopathological examination of whole slide images, accurate preopera

Cited by 0SourcePDFScholar
2024

Design and Visual Servoing Control of a Hybrid Dual-Segment Flexible Neurosurgical Robot for Intraventricular Biopsy

ICRA 2024poster

Traditional rigid endoscopes have challenges in flexibly treating tumors located deep in the brain, and low operability and fixed viewing angles limit its development. This study introduces a novel dual-segment flexible robotic endoscope MicroNeuro, designed to perform biopsies with dexterous surgic…

Cited by 3SourceScholar
2019

An Investigation into Neural Net Optimization via Hessian Eigenvalue Density

ICML 2019oral

To understand the dynamics of training in deep neural networks, we study the evolution of the Hessian eigenvalue density throughout the optimization process. In non-batch normalized networks, we observe the rapid appearance of large isolated eigenvalues in the spectrum, along with a surprising conce…

Cited by 383SourcePDFScholar
2018

Neumann Optimizer: A Practical Optimization Algorithm for Deep Neural Networks

ICLR 2018poster

Progress in deep learning is slowed by the days or weeks it takes to train large models. The natural solution of using more hardware is limited by diminishing returns, and leads to inefficient use of additional resources. In this paper, we present a large batch, stochastic optimization algorithm tha…

Cited by 24SourcePDFScholar
2018

Style Tokens: Unsupervised Style Modeling, Control and Transfer in End-to-End Speech Synthesis

ICML 2018oral

In this work, we propose “global style tokens” (GSTs), a bank of embeddings that are jointly trained within Tacotron, a state-of-the-art end-to-end speech synthesis system. The embeddings are trained with no explicit labels, yet learn to model a large range of acoustic expressiveness. GSTs lead to a…

Cited by 1059SourcePDFScholar
2018

Towards End-to-End Prosody Transfer for Expressive Speech Synthesis with Tacotron

ICML 2018oral

We present an extension to the Tacotron speech synthesis architecture that learns a latent embedding space of prosody, derived from a reference acoustic representation containing the desired prosody. We show that conditioning Tacotron on this learned embedding space results in synthesized audio that…

Cited by 749SourcePDFScholar